Reply to comment by G. L. Siscoe and K. D. Siebert on “Polar cap voltage saturation”
Bibliographic record
Abstract
[1] In their comment on our recent paper [MacDougall and Jayachandran, 2006], Siscoe and Siebert [2007] conclude that MHD simulations reproduce polar cap voltage saturation without needing to include region 2 currents. Their comments emphasize the importance of understanding the cause of polar cap voltage saturation in magnetosphere-ionosphere coupling studies. As with many magnetospheric phenomena, this may involve more than one process. The MHD simulations find it difficult to include or reproduce the proper strength of region 2 currents. Thus the MHD simulations are at present incapable of showing what effects region 2 current has on most magnetospheric behavior. [2] This inability to properly model region 2 current seems very unfortunate. Early studies by Iijima and Potemra [1976] and Fujii et al. [1981] found that most region 1 current ended up as region 2 current and these findings accord with one of our recent studies (J. W. MacDougall and P. T. Jayachandran, Winter cross polar cap current estimation, submitted to Advances in Space Research, 2007) of the polar cap currents. Thus region 2 current is actually a major feature of the magnetospheric system, of comparable importance to region 1 for some processes. Moreover, most of the studies which showed voltage saturation effects were during storm conditions [Hairston et al., 2003; Ober et al., 2003]. Under storm conditions the region 2 current probably becomes an even more important part of the system since it is directly associated with ring current intensification. Good resolution results from the Iridium constellation of satellites [Anderson et al., 2002, 2007] should finally give us direct measurements of the region 2 currents for inclusion/comparison with MHD models. Although the MHD models show saturation without region 2 currents being properly modeled, the region 2 currents are such an important part of the magnetospheric system that one hopes that future MHD development will properly show the relative importance of enhanced region 2 current versus other processes in causing the polar cap voltage saturation. [3] Wolfgang Baumjohann thanks the reviewers for their assistance in evaluating this paper.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.053 | 0.063 |
| Insufficient payload (model declined to judge) | 0.007 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".